Search results for: non linear analysis

Authors: M. Kislu Noman, Syed Mohammed Shamsul Islam, Shahriar Hassan, Raihana Pervin

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With the increasing rate of wireless devices and high bandwidth operations, wireless networking and communications are becoming over crowded. To cope with such crowdy and messy situation, massive MIMO is designed to work with hundreds of low costs serving antennas at a time as well as improve the spectral efficiency at the same time. TDD has been used for gaining beamforming which is a major part of massive MIMO, to gain its best improvement to transmit and receive pilot sequences. All the benefits are only possible if the channel state information or channel estimation is gained properly. The common methods to estimate channel matrix used so far is LS, MMSE and a linear version of MMSE also proposed in many research works. We have optimized these methods using genetic algorithm to minimize the mean squared error and finding the best channel matrix from existing algorithms with less computational complexity. Our simulation result has shown that the use of GA worked beautifully on existing algorithms in a Rayleigh slow fading channel and existence of Additive White Gaussian Noise. We found that the GA optimized LS is better than existing algorithms as GA provides optimal result in some few iterations in terms of MSE with respect to SNR and computational complexity.

Keywords: channel estimation, LMMSE, LS, MIMO, MMSE

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Authors: Zhidong Zhang, Zhi-Chao Zhang

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This study examines adolescent psychological and behavioral problems. The Achenbach systems of empirically based assessment (ASEBA) were used as the instrument. The problem framework consists of internal, external and social behavioral problems which are theoretically developed based on about 113 items plus relevant background variables. In this study, the sample consist of 1,975 sixth and seventh grade students in Northeast China. Stratified random sampling method was used to collect the data, meaning that samples were from different school districts, schools, and classes. The researchers looked at both macro and micro effect. Therefore, multilevel analysis techniques were used in the data analysis. The parts of the research results indicated that the background variables such as extracurricular activities were directly related to students’ internal problems.

Keywords: behavioral problems, anxious/depressed problems, internalizing problems, mental health, under-represented groups, empirically-based assessment, hierarchical modeling, ASEBA, multilevel analysis

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Authors: Hyeondal Jeong, Yoonjung Baek

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This study was carried out a meta-analysis on team workforce diversity and team outcomes. Using data from 3,534 teams in 13 studies conducted in team-level settings, we examined whether contextual factors at research local and team-size, influenced team outcomes of team workforce diversity. This meta-analytic examines the team workforce diversity and team outcomes. 13 studies included in the analysis are studies published from 2009 to 2014. We first examined the correlations between all types of diversity and team performance, significant result (Fisher`s Z = .112, k = 32, 95% CI = 0.039 to 0.183). After the analysis was conducted to moderating effect of research local (Republic of Korea=1, other area=0) and team-size. As a result, research local moderating effect had a significant but team-size was not supported. Based on the above findings suggest implications and future research directions.

Keywords: team workforce diversity, team outcomes, meta- analytic, cross-cultural research

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Authors: Abbas Vahedian, Rijun Shrestha, Keith Crews

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In recent years, fibre reinforced polymers as applications of strengthening materials have received significant attention by civil engineers and environmentalists because of their excellent characteristics. Currently, these composites have become a mainstream technology for strengthening of infrastructures such as steel, concrete and more recently, timber and masonry structures. However, debonding is identified as the main problem which limit the full utilisation of the FRP material. In this paper, a preliminary analysis of factors affecting bond strength of FRP-to-concrete and timber bonded interface has been conducted. A novel theoretical method through regression analysis has been established to evaluate these factors. Results of proposed model are then assessed with results of pull-out tests and satisfactory comparisons are achieved between measured failure loads (R² = 0.83, P < 0.0001) and the predicted loads (R² = 0.78, P < 0.0001).

Keywords: debonding, fibre reinforced polymers (FRP), pull-out test, stepwise regression analysis

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Authors: Giorgio Visentin, Inna S. Kalinina, Alexei A. Buchachenko

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In the ambit of intermolecular interactions, a combination rule is defined as a relation linking a potential parameter for the interaction of two unlike species with the same parameters for interaction pairs of like species. Some of their most exemplificative applications cover the construction of molecular dynamics force fields and dispersion-corrected density functionals. Here, an extended combination rule is proposed, relating the dipole-dipole dispersion coefficients for the interaction of like target species to the same coefficients for the interaction of the target and a set of partner species. The rule can be devised in two different ways, either by uniform discretization of the Casimir-Polder integral on a Gauss-Legendre quadrature or by relating the dynamic polarizabilities of the target and the partner species. Both methods return the same system of linear equations, which requires the knowledge of the dispersion coefficients for interaction between the partner species to be solved. The test examples show a high accuracy for dispersion coefficients (better than 1% in the pristine test for the interaction of Yb atom with rare gases and alkaline-earth metal atoms). In contrast, the rule does not ensure correct monotonic behavior of the dynamic polarizability of the target species. Acknowledgment: The work is supported by Russian Science Foundation grant # 17-13-01466.

Keywords: combination rule, dipole-dipole dispersion coefficient, Casimir-Polder integral, Gauss-Legendre quadrature

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Authors: Muna Al-Kalbani, Thuwayba Al Barwani, Otherine Neisler, Hussain Alkharusi, David Clayton, Humaira Al-Sulaimani, Mohammad Khan, Hamad Al-Yahmadi

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This study describes the psychometric properties and factor structure of the University Readiness Survey (URS). Survey data were collected from sample of 2652 students from Sultan Qaboos University. Exploratory factor analysis identified ten significant factors underlining the structure. The results of Confirmatory factor analysis showed a good fit to the data where the indices for the revised model were χ2(df = 1669) = 6093.4; CFI = 0.900; GFI =0.926; PCLOSE = 1.00 and RMSAE = 0.030 where each of these indices were above threshold. The overall value of Cronbach’s alpha was 0.899 indicating that the instrument score was reliable. Results imply that the URS is a valid measure describing the college readiness pattern among Sultan Qaboos University students and the Arabic version could be used by university counselors to identify students’ readiness factors. Nevertheless, further validation of the of the USR is recommended.

Keywords: college readiness, confirmatory factor analysis, reliability, validity

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Authors: W. J. Zhang, Y. Q. Du, M. L. Wang

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Noninvasive diagnostics of diseases via breath analysis has attracted considerable scientific and clinical interest for many years and become more and more promising with the rapid advancement in nanotechnology and biotechnology. The volatile organic compounds (VOCs) in exhaled breath, which are mainly blood borne, particularly provide highly valuable information about individuals’ physiological and pathophysiological conditions. Additionally, breath analysis is noninvasive, real-time, painless and agreeable to patients. We have developed a wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) for the detection of a number of physiological indicators in breath. Eight DNA sequences were used to functionalize SWNT sensors to detect trace amount of methanol, benzene, dimethyl sulfide, hydrogen sulfide, acetone and ethanol, which are indicators of heavy smoking, excessive drinking, and diseases such as lung cancer, breast cancer, cirrhosis and diabetes. Our tests indicated that DNA functionalized SWNT sensors exhibit great selectivity, sensitivity, reproducibility, and repeatability. Furthermore, different molecules can be distinguished through pattern recognition enabled by this sensor array. Thus, the DNA-SWNT sensor array has great potential to be applied in chemical or bimolecular detection for the noninvasive diagnostics of diseases and health monitoring.

Keywords: breath analysis, diagnosis, DNA-SWNT sensor array, noninvasive

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Authors: Komeil Valipourian

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Urban advances and the growing need for developing infrastructures has increased the importance of deep excavations. In this study, after the introducing probability analysis as an important issue, an attempt has been made to apply it for the deep excavation project of Bangkok’s Metro as a case study. For this, the numerical probability model has been developed based on the Finite Difference Method and Monte Carlo sampling approach. The results indicate that disregarding the issue of probability in this project will result in an inappropriate design of the retaining structure. Therefore, probabilistic redesign of the support is proposed and carried out as one of the applications of probability analysis. A 50% reduction in the flexural strength of the structure increases the failure probability just by 8% in the allowable range and helps improve economic conditions, while maintaining mechanical efficiency. With regard to the lack of efficient design in most deep excavations, by considering geometrical and geotechnical variability, an attempt was made to develop an optimum practical design standard for deep excavations based on failure probability. On this basis, a practical relationship is presented for estimating the maximum allowable horizontal displacement, which can help improve design conditions without developing the probability analysis.

Keywords: numerical probability modeling, deep excavation, allowable maximum displacement, finite difference method (FDM)

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Authors: Illyas Md Isa, Maryam Musfirah Che Sobry, Mohamad Syahrizal Ahmad, Nurashikin Abd Azis

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A single-walled carbon nanotube (SWCNT) that has been modified with magnesium layered hydroxide 3-(4-methoxyphenyl)propionic acid nanocomposite was proposed for the determination of uric acid and bisphenol A by square wave voltammetry. The results obtained denote that MLH-MPP nanocomposites enhance the sensitivity of the voltammetry detection responses. The best performance is shown by the modified carbon nanotube paste electrode (CNTPE) with the composition of single-walled carbon nanotube: magnesium layered hydroxide 3-(4-methoxyphenyl)propionic acid nanocomposite at 100:15 (% w/w). The linear range where the sensor works well is within the concentration 1.0 10-7 – 1.0 10-4 and 3.0 10-7 – 1.0 10-4 for uric acid and bisphenol A respectively with the limit of detection of 1.0 10-7 M for both organics. The interferences of uric acid and bisphenol A with other organic were studied and most of them did not interfere. The results shown for each experimental parameter on the proposed CNTPE showed that it has high sensitivity, good selectivity, repeatability and reproducibility. Therefore, the modified CNTPE can be used for the determination of uric acid and bisphenol A in real samples such as blood, plastic bottles and foods.

Keywords: bisphenol A, magnesium layered hydroxide 3-(4-methoxyphenyl)propionic acid nanocomposite, Nanocomposite, uric acid

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Authors: Patrick May Mukonki

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KOV pit (Kamoto Oliveira Virgule) is located 10 km from Kolwezi town, one of the mineral rich town in the Lualaba province of the Democratic Republic of Congo. The KOV pit is currently operating under the Katanga Mining Limited (KML), a Glencore-Gecamines (a State Owned Company) join venture. Recently, the mine optimization process provided a life of mine of approximately 10 years withnice pushbacks using the Datamine NPV Scheduler software. In previous KOV pit studies, we recently outlined the impact of the accuracy of the geological information on a long-term mine plan for a big copper mine such as KOV pit. The approach taken, discussed three main scenarios and outlined some weaknesses on the geological information side, and now, in this paper that we are going to develop here, we are going to highlight, as an overview, those weaknesses, strengths and opportunities, in a global SWOT analysis. The approach we are taking here is essentially descriptive in terms of steps taken to optimize KOV pit and, at every step, we categorized the challenges we faced to have a better tradeoff between what we called strengths and what we called weaknesses. The same logic is applied in terms of the opportunities and threats. The SWOT analysis conducted in this paper demonstrates that, despite a general poor ore body definition, and very rude ground water conditions, there is room for improvement for such high grade ore body.

Keywords: mine planning, mine optimization, mine scheduling, SWOT analysis

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Authors: Kinga Anna Gajda

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The aim of the paper is presented the results of the research project titled: Regional or trans-regional cultural education using the example of museums. In the frame of the project there were prepared: Qualitative and quantitative analysis of the level of schools’ use of museum programs in the period 2010-2015; Qualitative and quantitative analysis of interprovincial co-operation between schools and cultural institutions; intevied and questionnaries. That was a research materials. Informal education may include classes that use visual culture - museum lessons. The paper will examine what range of programs is offered schools by the museums. On the basis of the conducted analysis, the paper will verify what programs addressing the schools are directly coincided with the material taught in schools or as a supplement to existing curriculum. The paper will answer the question is the museum-based education the part of school education, the teaching parallel or a separate category of teaching.

Keywords: museum-based education, school, parallel teaching, curriculum

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Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

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Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm

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Authors: Ebru Kaymaz, Aslı İlbay Hamamcı, Yakup Enes Garip, Samet Ay

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The use of hydrogen as a fuel is important for decreasing carbon emissions. For the steel industry, reducing carbon emissions is one of the most important agendas of recent times globally. Because of the Paris Agreement requirements, European steel industry studies on green steel production. Although many literature reviews have analyzed this topic from technological and hydrogen based ironmaking, there are very few studies focused on patents of decarbonize parts of the steel industry. Hence, this study focus on technological progress of hydrogen based ironmaking and on understanding the main trends through patent data. All available patent data were collected from Questel Orbit. The trend analysis of more than 900 patent documents has been carried out by using Questel Orbit Intellixir to analyze a large number of data for scientific intelligence.

Keywords: hydrogen based ironmaking, DRI, direct reduction, carbon emission, steelmaking, patent analysis

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Authors: Anita Richter

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Innovation is one of the key foundations of competitive advantage, generating growth and welfare worldwide. Consequently, all firms should innovate to bring new ideas to the market. Innovation is a vital growth driver, particularly for transition countries to move towards knowledge-based, high-income economies. However, numerous barriers, such as financial, regulatory or infrastructural constraints prevent, in particular, new and small firms in transition countries from innovating. Thus SMEs’ innovation output may benefit substantially from government support. This research paper aims to assess the effect of government interventions on innovation activities in SMEs in emerging countries. Until now academic research related to the innovation policies focused either on single country and/or high-income countries assessments and less on cross-country and/or low and middle-income countries. Therefore the paper seeks to close the research gap by providing empirical evidence from 8,500 firms in 15 transition countries (Eastern Europe, South Caucasus, South East Europe, Middle East and North Africa). Using firm-level data from the Business Environment and Enterprise Performance Survey of the World Bank and EBRD and policy data from the SME Policy Index of the OECD, the paper investigates how government interventions affect SME’s likelihood of investing in any technological and non-technological innovation. Using the Standard Linear Regression, the impact of government interventions on SMEs’ innovation output and R&D activities is measured. The empirical analysis suggests that a firm’s decision to invest into innovative activities is sensitive to government interventions. A firm’s likelihood to invest into innovative activities increases by 3% to 8%, if the innovation eco-system noticeably improves (measured by an increase of 1 level in the SME Policy Index). At the same time, a better eco-system encourages SMEs to invest more in R&D. Government reforms in establishing a dedicated policy framework (IP legislation), institutional infrastructure (science and technology parks, incubators) and financial support (public R&D grants, innovation vouchers) are particularly relevant to stimulate innovation performance in SMEs. Particular segments of the SME population, namely micro and manufacturing firms, are more likely to benefit from an increased innovation framework conditions. The marginal effects are particularly strong on product innovation, process innovation, and marketing innovation, but less on management innovation. In conclusion, government interventions supporting innovation will likely lead to higher innovation performance of SMEs. They increase productivity at both firm and country level, which is a vital step in transitioning towards knowledge-based market economies.

Keywords: innovation, research and development, government interventions, economic development, small and medium-sized enterprises, transition countries

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Authors: Alyaa M. Younes, Nermine Harraz, Mohammad H. Elwany

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Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.

Keywords: accelerated life test, inverse power law, lithium-ion battery, reliability evaluation, Weibull distribution

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Authors: Ljiljana Seric, Vladimir Divic, Marin Bugaric

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This paper presents methodology for spatial analysis of GIS data that is used for assessing the microlocation risk index from potential damages of high winds. The analysis is performed on freely available GIS data comprising information about wind load, terrain cover and topography of the area. The methodology utilizes the legislation of Eurocode norms for determination of wind load of buildings and constructions. The core of the methodology is adoption of the wind load parameters related to location on geographical spatial grid. Presented work is a part of the Wind Risk Project, supported by the European Commission under the Civil Protection Financial Instrument of the European Union (ECHO). The partners involved in Wind Risk project performed Wind Risk assessment and proposed action plan for three European countries – Slovenia, Croatia and Germany. The proposed method is implemented in GRASS GIS open source GIS software and demonstrated for Case study area of wider area of Split, Croatia. Obtained Wind Risk Index is visualized and correlated with critical infrastructures like buildings, roads and power lines. The results show good correlation between high Wind Risk Index with recent incidents related to wind.

Keywords: Eurocode norms, GIS, spatial analysis, wind distribution, wind risk

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Authors: T. B. Anil Kumar, Mallikarjun Hiremath, V. Ramachandra

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The present experimental investigation deals with the quality performance analysis of cement concrete with 0, 15 and 25% fly ash and 0, 0.2, 0.4 and 0.6% of polypropylene fibers by weight of cement. The various test parameters like workability, unit weight, compressive strength, flexural strength, split tensile strength and abrasion resistance are detailed in the analysis. The compressive strength of M40 grade concrete attains higher value by the replacement of cement by 15% fly ash and at 0.4% PP after 28 and 56 days of curing. Higher flexural strength of concrete was observed by the replacement of cement by 15% fly ash with 0.2% PP after 28 and 56 days of curing. Similarly, split tensile strength value also increases and attains higher value by the replacement of cement by 15% fly ash with 0.4% PP after 28 and 56 days of curing. The percentage of wear gets reduced to 30 to 33% by the addition of fibers at 0.2%, 0.4% and 0.6% in cement concrete replaced by 15 and 25% fly ash. Hence, it is found that the pavement thickness gets reduced up to 20% when compared with plain concrete slab by the 15% fly ash treated with 0.2% PP fibers and also reduced up to 27% of surface course cost.

Keywords: cement, fly ash, polypropylene fiber, pavement design, cost analysis

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Authors: Amrutha Venugopal, Rabee Rustum

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In spite of huge investments and the vital role infrastructure plays in the economy of UAE, the country has not yet developed an assessment scheme to measure the sustainability of infrastructure projects/development. The aim of this study was to develop a sustainability rating system for infrastructure projects in UAE using weighted indicator scoring. The identification of the list of 66 indicators was done by content analysis. The sources of content analysis were from government guidelines, research literature and sustainability rating system for infrastructure projects namely BCA Greenmark for Infrastructure (Singapore), ISCA (Australia) and Envision (USA). These indicators were shortlisted based on their relevance in the UAE. A mixture of qualitative and quantitative research methods is utilized to find the weightage to be applied to the indicators and to find suggestive measures to improve infrastructure sustainability in this region. Interviews and surveys were conducted with a good mix of experts from the industry. The data collected from the interviews were collated to provide suggestive measures for improving infrastructure sustainability. The collected survey data were analyzed using statistical analysis techniques to find the indicator weighing. The indicators were shortlisted by 75% to minimize the effort and investment into the process. The weighing of the deleted indicators was distributed among the critical clusters identified by Pareto analysis. Finally a simple Microsoft Excel tool was developed as the rating tool by using the calculated weighing for the indicators.

Keywords: infrastructure, rating system, suggestive measures, sustainability, UAE

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Authors: Herlandson C. Moura, Jorge H. Bidinotto, Eduardo M. Belo

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The present work proposes the development of an adaptive control system which enables the suppression of Pilot Induced Oscillations (PIO) in Digital Fly-By-Wire (DFBW) aircrafts. The proposed system consists of a Modified Model Reference Adaptive Control (M-MRAC) integrated with the Gain Scheduling technique. The PIO oscillations are detected using a Real Time Oscillation Verifier (ROVER) algorithm, which then enables the system to switch between two reference models; one in PIO condition, with low proneness to the phenomenon and another one in normal condition, with high (or medium) proneness. The reference models are defined in a closed loop condition using the Linear Quadratic Regulator (LQR) control methodology for Multiple-Input-Multiple-Output (MIMO) systems. The implemented algorithms are simulated in software implementations with state space models and commercial flight simulators as the controlled elements and with pilot dynamics models. A sequence of pitch angles is considered as the reference signal, named as Synthetic Task (Syntask), which must be tracked by the pilot models. The initial outcomes show that the proposed system can detect and suppress (or mitigate) the PIO oscillations in real time before it reaches high amplitudes.

Keywords: adaptive control, digital Fly-By-Wire, oscillations suppression, PIO

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Authors: Mashood C., Abdul Vahid K., Ashique C. K.

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The technology is growing beyond human expectation. Internet is one of very sophisticated product of the information technology. It has various advantages like connecting the world, simplifying the difficult tasks done in past etc. Simultaneously it has demerits also; that is lack of authenticity and internet addiction. To find out the problems of internet addiction, a study conducted among the Postgraduate students of Pondicherry University and collected 454 samples. The study strictly focused to identify the internet addiction among students, influence and interdependence of personality on internet addiction among first years and second years. To evaluate this, we used two major analysis, these are Confirmatory Factor Analysis (CFA) to predict the internet addiction with the observed data and Logistic Regression to identify the difference between first years and second years in the case of internet addiction. Before applying to the core analysis, the data applied to some preliminary tests to check the model fit. The empirical findings shows that , the students of Pondicherry University are very much addicted to the internet, But there is no such huge difference between first years and second years in case of internet addiction.

Keywords: internet addiction, students, Pondicherry University, empirical study

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Authors: Hamed Alizadeh Dashagholi, Hossein Yousefi-Banaem, Mina Naeimi

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Current study established for EEG signal analysis in patients with language disorder. Language disorder can be defined as meaningful delay in the use or understanding of spoken or written language. The disorder can include the content or meaning of language, its form, or its use. Here we applied Z-score, power spectrum, and coherence methods to discriminate the language disorder data from healthy ones. Power spectrum of each channel in alpha, beta, gamma, delta, and theta frequency bands was measured. In addition, intra hemispheric Z-score obtained by scoring algorithm. Obtained results showed high Z-score and power spectrum in posterior regions. Therefore, we can conclude that peoples with language disorder have high brain activity in frontal region of brain in comparison with healthy peoples. Results showed that high coherence correlates with irregularities in the ERP and is often found during complex task, whereas low coherence is often found in pathological conditions. The results of the Z-score analysis of the brain dynamics showed higher Z-score peak frequency in delta, theta and beta sub bands of Language Disorder patients. In this analysis there were activity signs in both hemispheres and the left-dominant hemisphere was more active than the right.

Keywords: EEG, electroencephalography, coherence methods, language disorder, power spectrum, z-score

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Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

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Authors: Shrabani Ghosh

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Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

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Authors: Emre Ipekci Cetin, Ebru Tarcan Icigen

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Personnel selection process is considered as one of the most important and most difficult issues in human resources management. At the stage of personnel selection, the applicants are handled according to certain criteria, the candidates are dealt with, and efforts are made to select the most appropriate candidate. However, this process can be more complicated in terms of the managers who will carry out the staff selection process. Candidates should be evaluated according to different criteria such as work experience, education, foreign language level etc. It is crucial that a rational selection process is carried out by considering all the criteria in an integrated structure. In this study, the problem of choosing the front office manager of a 5 star accommodation enterprise operating in Antalya is addressed by using multi-criteria decision-making methods. In this context, SWARA (Step-wise weight assessment ratio analysis) and MOORA (Multi-Objective Optimization on the basis of ratio analysis) methods, which have relatively few applications when compared with other methods, have been used together. Firstly SWARA method was used to calculate the weights of the criteria and subcriteria that were determined by the business. After the weights of the criteria were obtained, the MOORA method was used to rank the candidates using the ratio system and the reference point approach. Recruitment processes differ from sector to sector, from operation to operation. There are a number of criteria that must be taken into consideration by businesses in accordance with the structure of each sector. It is of utmost importance that all candidates are evaluated objectively in the framework of these criteria, after these criteria have been carefully selected in the selection of suitable candidates for employment. In the study, staff selection process was handled by using SWARA and MOORA methods together.

Keywords: accommodation establishments, human resource management, multi-objective optimization on the basis of ratio analysis, multi-criteria decision making, step-wise weight assessment ratio analysis

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Authors: Prince Dacosta Aboagye, Ayyoob Sharifi

Abstract:

Cities respond to climate concerns mainly through their climate action plans (CAPs). A comprehensive content analysis of the dynamics in existing urban CAPs is not well represented in the literature. This literature void presents a difficulty in appreciating the strengths and weaknesses of urban CAPs. Here, we perform a qualitative content analysis (QCA) on CAPs from 278 cities worldwide and use text-mining tools to map and visualize the relevant data. Our analysis showed a decline in the number of CAPs developed and published following the global COVID-19 lockdown period. Evidently, megacities are leading the deep decarbonisation agenda. We also observed a transition from developing mainly mitigation-focused CAPs pre-COP21 to both mitigation and adaptation CAPs. A lack of inclusiveness in local climate planning was common among European and North American cities. The evidence is a catalyst for understanding the trends in existing urban CAPs to shape future urban climate planning.

Keywords: urban, climate action plans, strengths, weaknesses

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Authors: Tsoi Kim Ming, Yu King Pong

Abstract:

Background: With powered wheelchair, patients can travel more easily and conveniently. However, some patients suffer from other difficulties, such as visual impairment, cognitive disorder, or psychological issues, which make them unable to control powered wheelchair safely. Purpose: Therefore, those patients are required to complete a comprehensive driving training by therapists on confined area, which simulates narrow paths in daily live. During the training, therapists will give series of driving instruction to patients, which may be unaware of patients crossing out the boundary of area. To facilitate the training, it is needed to develop a device to provide warning to patients during training Method: We adopt LIDAR for distance sensing started from center of confined area. Then, we program the LIDAR with linear geometry to remember each side of the area. The LIDAR will sense the location of wheelchair continuously. Once the wheelchair is driven out of the boundary, audio alert will be given to patient. Result: Patients can pay their attention to the particular driving situation followed by audio alert during driving training, which can learn how to avoid out of boundary in similar situation next time. Conclusion: Instead of only instructed by therapist, the LIDAR can facilitate the powered wheelchair training by patients actively pay their attention to driving situation. After training, they are able to control the powered wheelchair safely when facing difficult and narrow path in real life.

Keywords: PWC, training, rehab, AT

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Authors: Mahiout Tassadit

Abstract:

As part of the study of a compliance and quality aspect concerning one of the plant-based products: drugs for herbal teas sold in pharmacies, a survey targeting: the general population (100 people of different age groups) as well as dispensary pharmacists (40 pharmacists from rural or urban areas) of the wilaya of Tizi-Ouzou (central Algeria) was carried out followed by a macroscopic and microscopic analysis of 4 samples of the said drugs, the survey carried out using two questionnaires, the data of which were collected and then analyzed, made it possible to estimate the population's use of herbal products and medicinal plants, and the place occupied by herbal medicine in our pharmacies. The second part made it possible to control and evaluate the information present on the packaging of drugs for herbal teas; anomalies concerning the packaging, labeling and composition of these products were noted. As a result, it is more than necessary to establish regulations for this type of product; the community pharmacist again places himself as an essential element for the proper dispensation of these remedies.

Keywords: drugs, herbal teas, macroscopic analysis, microscopic analysis

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Authors: Zsolt Szilvágyi, Jakub Panuska, Orsolya Kegyes-Brassai, Ákos Wolf, Péter Tildy, Richard P. Ray

Abstract:

Near-surface loose sediments and local ground conditions in general have a major influence on seismic response of structures. It is a difficult task to model ground behavior in seismic soil-structure-foundation interaction problems, fully account for them in seismic design of structures, or even properly consider them in seismic hazard assessment. In this study, we focused on applying seismic soil investigation methods, used for determining soil stiffness and damping properties, to response analysis used in seismic design. A site in Budapest, Hungary was investigated using Multichannel Analysis of Surface Waves, Seismic Cone Penetration Tests, Bender Elements, Resonant Column and Torsional Shear tests. Our aim was to compare the results of the different test methods and use the resulting soil properties for 1D ground response analysis. Often in practice, there are little-to no data available on dynamic soil properties and estimated parameters are used for design. Therefore, a comparison is made between results based on estimated parameters and those based on detailed investigations. Ground response results are also compared to Eurocode 8 design spectra.

Keywords: MASW, resonant column test, SCPT, site response analysis, torsional shear test

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Authors: Hanady Hamdallah, H. Elyse Ireland, John H. H. Williams

Abstract:

Conjugated linoleic acid (CLA) is a food supplement that is reported to have multiple beneficial health effects, including being anti-carcinogenic, anti-inflammatory and anti-obesity. Animal studies have shown a significant anti-obesity effect of CLA, but results in humans were inconsistent, where some of the studies found an anti-obesity effect while other studies failed to find any decline in obesity markers after CLA supplementation. This meta-analysis aimed to determine if oral CLA supplementation has been shown to reduce obesity related markers in women. Pub Med, Cochrane Library, and Google Scholar were used to identify the eligible trials using two main searching strategies: the first one was to search eligible trials using keywords 'Conjugated linoleic acid', 'CLA', 'Women', and the second strategy was to extract the eligible trials from previously published systematic reviews and meta-analyses. The eligible trials were placebo control trials where women supplemented with CLA mixture in the form of oral capsules for 6 months or less. Also, these trials provided information about body composition expressed as body weight (BW), body mass index (BMI), total body fat (TBF), percentage body fat (BF %), and/ or lean body mass (LBM). The quality of each included study was assessed using both JADAD scale and an adapted CONSERT checklist. Meta-analysis of 8 eligible trials showed that CLA supplementation was significantly associated with reduced BW (Mean ± SD, 1.2 ± 0.26 kg, p < 0.001), BMI (0.6 ± 0.13kg/m², p < 0.001) and TBF (0.76 ± 0.26 kg, p= 0.003) in women, when supplemented over 6-16 weeks. Subgroup meta-analysis demonstrated a significant reduction in BW (1.29 ± 0.31 kg, p < 0.001), BMI (0.60 ± 0.14 kg/m², p < 0.001) and TBF (0.82 ± 0.28 kg, p= 0.003) in the trials that had recruited overweight-obese women. The second subgroup meta-analysis, that considered the menopausal status of the participants, found that CLA was significantly associated with reduced BW (1.35 ± 0.37 kg, p < 0.001; 1.05 ± 0.36 kg, p= 0.003) and BMI (0.50 ± 0.17 kg/m², p= 0.003; 0.75 ± 0.2 kg/m², p < 0.001) in both pre and post-menopausal age women, respectively. A reduction in TBF (1.09 ± 0.37 kg, p= 0.003) was only significant in post-menopausal women. Interestingly, CLA supplementation was associated with a significant reduction in BW (1.05 ± 0.35 kg, p< 0.003), BMI (0.73 ± 0.2 kg/m², p < 0.001) and TBF (1.07 ± 0.36 kg, p= 0.003) in the trials without lifestyle monitoring or interventions. No significant effect of CLA on LBM was detected in this meta-analysis. This meta-analysis suggests a moderate anti-obesity effect of CLA on BW, BMI and TBF reduction in women, when supplemented over 6-16 weeks, particularly in overweight-obese women and post-menopausal women. However, this finding requires careful interpretation due to several issues in the designs of available CLA supplementation trials. More well-designed trials are required to confirm this meta-analysis results.

Keywords: body composition, body mass index, body weight, conjugated linoleic acid

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Authors: Hyung-Joon Kim, Jin-Young Park

Abstract:

Energy dissipating devices (EDDs) have become more popular as seismic-force-resisting systems for building structures. However, there is little information on the collapse capacities of frames employing EDDs which are an important criterion for their seismic design. This study investigates the collapse capacities of steel frames with TADAS hysteric energy dissipative devices (HEDDs) that become an alternative to steel braced frames. To do this, 5-story steel ordinary concentrically braced frame and steel frame with HEDDs are designed and modeled. Nonlinear dynamic analyses and incremental dynamic analysis with 40 ground motions scaled to maximum considered earthquake are carried out. It is shown from analysis results that the significant enhancement in terms of the collapse capacities is found due to the introduction HEDDs.

Keywords: collapse capacity, incremental dynamic analysis, steel braced frame, TADAS hysteric energy dissipative device

Procedia PDF Downloads 484